Emojis help millions of humans inject emotional nuance into their online conversation every day. They let your friends, family and lovers know that a critical remark was meant in jest or that what might be taken as a throwaway comment is actually a sincere expression of deep disapproval that can't be ignored.

Now, MIT’s Technology Review magazine reports, researchers have used the popular icons to train an algorithm to spot sarcasm. And it’s better at doing so than humans.

“An algorithm MIT researchers developed to analyze tweets can now detect sarcasm, and emotional subtext in general, better than most people,” the magazine’s report says.

The tool, called DeepMoji, uses deep learning to recognize when tweets are likely to be sarcastic. Researchers had the algorithm read some 1.2 billion tweets containing a combination of 64 emojis. After first having the system predict which emoji would be associated with a given tweet based on its emotional tone, they then taught the program to identify sarcasm by using a prepared data set. The algorithm that had been ready-schooled in emotion via emojis was better at detecting sarcasm than an untrained equivalent.

DeepMoji has an 82-percent accuracy rate at identifying sarcasm, which puts it just above human volunteers recruited via the crowdsourcing site Mechanical Turk, who had a 76-percent success rate.

“Because we can’t use intonation in our voice or body language to contextualize what we are saying, emoji are the way we do it online,” said Iyad Rahwan, an associate professor the MIT Media lab who co-developed the algorithm with Bjarke Felbo. “The neural network learned the connection between a certain kind of language and an emoji.”

“It might be that it’s learning all the different slang,” Felbo said. “People have very interesting uses of language [on Twitter]—let’s put it that way.”

On the algorithm’s website you can test its emoji-linking function; it will automatically add emojis to any text you submit.